Kathleen Golle, Thomas Mühlbauer, Ditmar Wick, Urs Granacher

• Background Generating percentile values is helpful for the identification of children with specific fitness characteristics (i. e., low or high fitness level) to set appropriate fitness goals (i. e., fitness/ health promotion and/or long-term youth athlete development). Thus, the aim of this longitudinal study was to assess physical fitness development in healthy children aged 9-12 years and to compute sex-and age-specific percentile values. Methods Two-hundred and forty children (88 girls, 152 boys) participated in this study and were tested for their physical fitness. Physical fitness was assessed using the 50-m sprint test (i. e., speed), the 1-kg ball push test, the triple hop test (i. e., upper-and lower-extremity muscular power), the stand-and-reach test (i. e., flexibility), the star run test (i. e., agility), and the 9-min run test (i. e., endurance). Age-and sex-specific percentile values (i. e., P-10 to P-90) were generated using the Lambda, Mu, and Sigma method. Adjusted (for change in body weight, height, and baselineBackground Generating percentile values is helpful for the identification of children with specific fitness characteristics (i. e., low or high fitness level) to set appropriate fitness goals (i. e., fitness/ health promotion and/or long-term youth athlete development). Thus, the aim of this longitudinal study was to assess physical fitness development in healthy children aged 9-12 years and to compute sex-and age-specific percentile values. Methods Two-hundred and forty children (88 girls, 152 boys) participated in this study and were tested for their physical fitness. Physical fitness was assessed using the 50-m sprint test (i. e., speed), the 1-kg ball push test, the triple hop test (i. e., upper-and lower-extremity muscular power), the stand-and-reach test (i. e., flexibility), the star run test (i. e., agility), and the 9-min run test (i. e., endurance). Age-and sex-specific percentile values (i. e., P-10 to P-90) were generated using the Lambda, Mu, and Sigma method. Adjusted (for change in body weight, height, and baseline performance) age-and sex-differences as well as the interactions thereof were expressed by calculating effect sizes (Cohen's d). Results Significant main effects of Age were detected for all physical fitness tests (d = 0.40-1.34), whereas significant main effects of Sex were found for upper-extremity muscular power (d = 0.55), flexibility (d = 0.81), agility (d = 0.44), and endurance (d = 0.32) only. Further, significant Sex by Age interactions were observed for upper-extremity muscular power (d = 0.36), flexibility (d = 0.61), and agility (d = 0.27) in favor of girls. Both, linear and curvilinear shaped curves were found for percentile values across the fitness tests. Accelerated (curvilinear) improvements were observed for upper-extremity muscular power (boys: 10-11 yrs; girls: 9-11 yrs), agility (boys: 9-10 yrs; girls: 9-11 yrs), and endurance (boys: 9-10 yrs; girls: 9-10 yrs). Tabulated percentiles for the 9-min run test indicated that running distances between 1,407-1,507 m, 1,479-1,597 m, 1,423-1,654 m, and 1,433-1,666 m in 9-to 12-year-old boys and 1,262-1,362 m, 1,329-1,434 m, 1,392-1,501 m, and 1,415-1,526 m in 9-to 12-year-old girls correspond to a "medium" fitness level (i. e., P-40 to P-60) in this population. Conclusions The observed differences in physical fitness development between boys and girls illustrate that age- and sex-specific maturational processes might have an impact on the fitness status of healthy children. Our statistical analyses revealed linear (e. g., lower-extremity muscular power) and curvilinear (e. g., agility) models of fitness improvement with age which is indicative of timed and capacity-specific fitness development pattern during childhood. Lastly, the provided age-and sex-specific percentile values can be used by coaches for talent identification and by teachers for rating/ grading of children's motor performance.…